正在加载视频...

视频加载失败

返回首页

become a quant trader on Polymarket for free. these three GitHub repos close the whole cycle a friend from a well-known hedge fund sent me the list, said they keep it in their working set and it adds up on the capital. what surprised me is that all three...

xmayeth's profile picture

may.crypto {🦅}

39,142 subscribers

20,266 次观看 • 4 天前 •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓
0:15

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓

Argona

21,946 次观看 • 21 天前

A lesson for every Polymarket bot developer: I built a strategy that looked perfect on paper. Backtested it. Looked like a winner. Almost went live. Then i actually measured real costs. Strategy was dead before the first trade. And this is what bot building on Polymarket actually looks like. Here is what happened (and what you MUST know): Backtested mean reversion on crypto dips. SOL came back at +44% return and 70.5% win rate. Beautiful clean curve. Looked ready to ship. Then i measured real round-trip costs on SOL flash dips. Backtest assumed 0.45% in fees and slippage. Reality was 1.44%. Strategy stops working at 0.70%. Starting again. But the lesson was worth more than any profit the strategy could have made. Here is what i actually learned: Taking a dip with a market order means you eat the spread the dip just created. The volatility making your signal is the same volatility destroying your fill. You see the opportunity. You enter. You already lost. But resting a limit order below market and letting the dip come to you? You collect the maker rebate instead. Same thesis. Completely opposite execution. One bleeds money, one prints it. That one realization changed how i think about bot strategy entirely. 180 strategies tested to get there. 179 dead. That is not failure. That is how you find the 5 that actually work. Building a bot on Polymarket is not about finding a magic strategy. It is about eliminating every wrong answer until only the right one is left.
0:11

A lesson for every Polymarket bot developer: I built a strategy that looked perfect on paper. Backtested it. Looked like a winner. Almost went live. Then i actually measured real costs. Strategy was dead before the first trade. And this is what bot building on Polymarket actually looks like. Here is what happened (and what you MUST know): Backtested mean reversion on crypto dips. SOL came back at +44% return and 70.5% win rate. Beautiful clean curve. Looked ready to ship. Then i measured real round-trip costs on SOL flash dips. Backtest assumed 0.45% in fees and slippage. Reality was 1.44%. Strategy stops working at 0.70%. Starting again. But the lesson was worth more than any profit the strategy could have made. Here is what i actually learned: Taking a dip with a market order means you eat the spread the dip just created. The volatility making your signal is the same volatility destroying your fill. You see the opportunity. You enter. You already lost. But resting a limit order below market and letting the dip come to you? You collect the maker rebate instead. Same thesis. Completely opposite execution. One bleeds money, one prints it. That one realization changed how i think about bot strategy entirely. 180 strategies tested to get there. 179 dead. That is not failure. That is how you find the 5 that actually work. Building a bot on Polymarket is not about finding a magic strategy. It is about eliminating every wrong answer until only the right one is left.

Oracle Boar

14,379 次观看 • 4 个月前

I used Claude Code to build and automate a legitimate quant trading strategy. The framework I built is based on the GARCH model, and it's one of the most-used trading models by real quant desks. The crazy thing is, I just completely open-sourced the GitHub repo. It contains: a Pine Script indicator for TradingView that loads the quant strategy in real time, complete installation instructions, a reusable Claude Skill & more. This is probably the most-valuable thing I've shared on 𝕏 in 2026. →
0:10

I used Claude Code to build and automate a legitimate quant trading strategy. The framework I built is based on the GARCH model, and it's one of the most-used trading models by real quant desks. The crazy thing is, I just completely open-sourced the GitHub repo. It contains: a Pine Script indicator for TradingView that loads the quant strategy in real time, complete installation instructions, a reusable Claude Skill & more. This is probably the most-valuable thing I've shared on 𝕏 in 2026. →

Miles Deutscher

87,456 次观看 • 1 个月前

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓
0:15

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓

Argona

32,475 次观看 • 1 个月前

$5 into $500,000 on polymarket nobody is talking about him 17,000 predictions. 100% win rate. one market category: Up/Down. $180 → $8,400 $250 → $8,000 he doesnt pick markets. he doesnt guess directions. he finds the bets with the highest probability of already being correct and just keeps buying them before they close sounds obvious. but you cant do it manually by the time you see the opportunity the window is already closing a bot can. and this one does it 17,000 times. every trade is public: $5 starting capital $500,000 result zero losses across 17,000 trades the math on this profile alone is worth studying for a week open it. look at the entry prices. look at the timing. everything you need to understand the strategy is right there on chain most people will screenshot this and forget the ones who open the profile today will understand something that took this guy 17,000 trades to prove
0:33

$5 into $500,000 on polymarket nobody is talking about him 17,000 predictions. 100% win rate. one market category: Up/Down. $180 → $8,400 $250 → $8,000 he doesnt pick markets. he doesnt guess directions. he finds the bets with the highest probability of already being correct and just keeps buying them before they close sounds obvious. but you cant do it manually by the time you see the opportunity the window is already closing a bot can. and this one does it 17,000 times. every trade is public: $5 starting capital $500,000 result zero losses across 17,000 trades the math on this profile alone is worth studying for a week open it. look at the entry prices. look at the timing. everything you need to understand the strategy is right there on chain most people will screenshot this and forget the ones who open the profile today will understand something that took this guy 17,000 trades to prove

kiruwaaaa

27,401 次观看 • 5 个月前

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.
0:18

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.

Miles Deutscher

56,625 次观看 • 1 个月前

China's central bank has now bought gold for 19 months straight, the largest official buyer on earth. And this week, as gold broke 4,000 dollars, China's biggest banks moved to push ordinary Chinese out of leveraged gold trading, with at least one warning it will liquidate any position not closed by month-end. Both are true at once, and together they explain what this crash really is. Start with what is being banned, because the words matter. ICBC and a string of other banks are shutting down retail trading in what the Chinese themselves call paper gold, the margined, leveraged contracts where you bet on the price without ever owning a bar. Some banks lifted the margin requirement to 140 percent to choke the leverage off before closing the products outright. Physical gold, meanwhile, stays wide open. Coins, bars, savings plans, ETFs, all fine. It is only the paper, the leverage, the casino, that is being shut, the last step in a five-year retreat that the crash just finished. Officially this is about protecting small investors, and that part is real. The same kind of leverage wiped out a wave of Chinese retail in a 2020 commodity blowup. But set the ban beside what the state is doing and something larger comes into view. While its citizens are pushed out of the paper, the People's Bank of China has spent those same 19 months buying the physical metal, more than two thousand three hundred tonnes of it now, accumulating straight through a 28 percent crash that scared everyone else out. Beijing is not trading gold. It is hoarding it. That is the strategy in one frame. China looked at the two things both called gold, the paper bet and the physical bar, and made a choice no Western government would make. It is taking the metal for the state and closing the casino for everyone else. The reason sits in a single date. 2022, when Russia's reserves were frozen with a keystroke. That taught every country outside the Western system one lesson: dollars in an account can be switched off, gold in your own vault cannot. So China is building its monetary independence out of the one asset nobody can freeze, and it does not want that foundation in the hands of leveraged traders who panic-sell in a crash, or priced by a paper market it does not control. Watch this month and the two worlds split in real time. Western investors were forced out of their gold by margin calls and a rate scare. China's central bank bought that exact dip with both hands. One side treats gold as a trade. The other treats it as the floor under a currency. The West is selling paper gold and calling it a crash. China is buying physical gold and calling it a foundation. In ten years, only one of them will look like it understood what gold was for. The metal is already moving to that side.
0:10

China's central bank has now bought gold for 19 months straight, the largest official buyer on earth. And this week, as gold broke 4,000 dollars, China's biggest banks moved to push ordinary Chinese out of leveraged gold trading, with at least one warning it will liquidate any position not closed by month-end. Both are true at once, and together they explain what this crash really is. Start with what is being banned, because the words matter. ICBC and a string of other banks are shutting down retail trading in what the Chinese themselves call paper gold, the margined, leveraged contracts where you bet on the price without ever owning a bar. Some banks lifted the margin requirement to 140 percent to choke the leverage off before closing the products outright. Physical gold, meanwhile, stays wide open. Coins, bars, savings plans, ETFs, all fine. It is only the paper, the leverage, the casino, that is being shut, the last step in a five-year retreat that the crash just finished. Officially this is about protecting small investors, and that part is real. The same kind of leverage wiped out a wave of Chinese retail in a 2020 commodity blowup. But set the ban beside what the state is doing and something larger comes into view. While its citizens are pushed out of the paper, the People's Bank of China has spent those same 19 months buying the physical metal, more than two thousand three hundred tonnes of it now, accumulating straight through a 28 percent crash that scared everyone else out. Beijing is not trading gold. It is hoarding it. That is the strategy in one frame. China looked at the two things both called gold, the paper bet and the physical bar, and made a choice no Western government would make. It is taking the metal for the state and closing the casino for everyone else. The reason sits in a single date. 2022, when Russia's reserves were frozen with a keystroke. That taught every country outside the Western system one lesson: dollars in an account can be switched off, gold in your own vault cannot. So China is building its monetary independence out of the one asset nobody can freeze, and it does not want that foundation in the hands of leveraged traders who panic-sell in a crash, or priced by a paper market it does not control. Watch this month and the two worlds split in real time. Western investors were forced out of their gold by margin calls and a rate scare. China's central bank bought that exact dip with both hands. One side treats gold as a trade. The other treats it as the floor under a currency. The West is selling paper gold and calling it a crash. China is buying physical gold and calling it a foundation. In ten years, only one of them will look like it understood what gold was for. The metal is already moving to that side.

Shanaka Anslem Perera ⚡

327,303 次观看 • 2 个月前

There is a "flash" bug in the One UI 7 Beta1 animation. In fact, there are at least three versions of this problem. Samsung seems to have not found it, so it has not been solved. You only need to open two apps in succession a little quickly (not particularly fast)，You will see a quick flicker in the picture. The first video is played at normal speed, and you can see a flash picture. The second video is a slow video, and you can see the moment when the soul of a page flashes in the ninth second. I call it the One UI 7 haunted event.
0:01

There is a "flash" bug in the One UI 7 Beta1 animation. In fact, there are at least three versions of this problem. Samsung seems to have not found it, so it has not been solved. You only need to open two apps in succession a little quickly (not particularly fast)，You will see a quick flicker in the picture. The first video is played at normal speed, and you can see a flash picture. The second video is a slow video, and you can see the moment when the soul of a page flashes in the ninth second. I call it the One UI 7 haunted event.

Ice Universe

120,758 次观看 • 1 年前

The world just paid $2 trillion for a rocket company that lost $4.9 billion last year. And the rockets are not why it lost the money. They are the only part making any. SpaceX went public Friday, the largest IPO in history. Up 19%, a $2 trillion valuation, Elon Musk the first trillionaire. Then you open the filing. Three businesses sit inside it. Starlink, the satellites, brought in $11.4 billion, 61% of all revenue, and $4.4 billion in profit. It is the only piece that earns a dollar. The rockets that land themselves run a small loss reinvesting in Starship. And the AI arm, Grok plus the app once called Twitter, folded in this February, lost $6.4 billion in a single year on $12.7 billion of spending. Read that again. The satellites pay for everything. The AI loses more than the satellites make. And the AI is the part the market fell in love with. It gets bolder. The prospectus claims a total market of $28.5 trillion, the largest any company has ever put in a filing. Larger than the GDP of the United States. That is the number underwriting a $2 trillion price tag built on a division bleeding $6 billion a year. Now the structure. About 4% of the company trades. That sliver sets the price for all of it. Musk is locked up for 366 days and holds roughly 80% of the votes. The public bought a company they cannot steer, priced on the one segment losing the most. This is the whole year in one ticker. The profit is satellites. The story is AI. The market bought the story. The rockets were never the risk. The risk is a $2 trillion price resting on the one bet that has yet to make a cent.
0:10

The world just paid $2 trillion for a rocket company that lost $4.9 billion last year. And the rockets are not why it lost the money. They are the only part making any. SpaceX went public Friday, the largest IPO in history. Up 19%, a $2 trillion valuation, Elon Musk the first trillionaire. Then you open the filing. Three businesses sit inside it. Starlink, the satellites, brought in $11.4 billion, 61% of all revenue, and $4.4 billion in profit. It is the only piece that earns a dollar. The rockets that land themselves run a small loss reinvesting in Starship. And the AI arm, Grok plus the app once called Twitter, folded in this February, lost $6.4 billion in a single year on $12.7 billion of spending. Read that again. The satellites pay for everything. The AI loses more than the satellites make. And the AI is the part the market fell in love with. It gets bolder. The prospectus claims a total market of $28.5 trillion, the largest any company has ever put in a filing. Larger than the GDP of the United States. That is the number underwriting a $2 trillion price tag built on a division bleeding $6 billion a year. Now the structure. About 4% of the company trades. That sliver sets the price for all of it. Musk is locked up for 366 days and holds roughly 80% of the votes. The public bought a company they cannot steer, priced on the one segment losing the most. This is the whole year in one ticker. The profit is satellites. The story is AI. The market bought the story. The rockets were never the risk. The risk is a $2 trillion price resting on the one bet that has yet to make a cent.

Shanaka Anslem Perera ⚡

722,071 次观看 • 2 个月前

whoever leaked this has bigger balls than sense someone at Anthropic hired 80 AI helpers onto one project, gave them twelve hours, and counted what came back usable: the two older models handed in 980 and 876 finished pieces of work, and almost none of it could be kept turns out the newest helpers did better for a reason nobody wants to hear: they went off into their own corners and stopped opening each other's work i ran two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Grok Bot is the version of this you can actually hire: a helper with a name, one job it owns, and nobody else allowed inside that job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in a normal chat, 3 moves: 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that is already taken save this, then open the piece below: what one hired helper is really worth, and the point where the next one starts taking it back ↓
0:15

whoever leaked this has bigger balls than sense someone at Anthropic hired 80 AI helpers onto one project, gave them twelve hours, and counted what came back usable: the two older models handed in 980 and 876 finished pieces of work, and almost none of it could be kept turns out the newest helpers did better for a reason nobody wants to hear: they went off into their own corners and stopped opening each other's work i ran two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Grok Bot is the version of this you can actually hire: a helper with a name, one job it owns, and nobody else allowed inside that job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in a normal chat, 3 moves: 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that is already taken save this, then open the piece below: what one hired helper is really worth, and the point where the next one starts taking it back ↓

Argona

447,680 次观看 • 21 天前

whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓
0:15

whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓

Argona

694,694 次观看 • 24 天前

You can make $600K. With a bot that earns $83 every hour, 24/7, no days off, 365 days straight. By buying both sides of the same match on Polymarket and locking profit before the game even starts. > The bot buys YES and NO simultaneously on sports markets. > When combined price is below $1 - profit is locked instantly. > 7,877 trades. > $619K in 12 months. Check the wallet here: I reverse-engineered every trade and rebuilt the full logic in Claude Opus 4.6. The strategy, the math, both arb types, the exact 5-step bot architecture - all in the article. Feed it to your OpenClaw, let it spec the bot for Claude Opus 4.6, and you are set.
0:15

You can make $600K. With a bot that earns $83 every hour, 24/7, no days off, 365 days straight. By buying both sides of the same match on Polymarket and locking profit before the game even starts. > The bot buys YES and NO simultaneously on sports markets. > When combined price is below $1 - profit is locked instantly. > 7,877 trades. > $619K in 12 months. Check the wallet here: I reverse-engineered every trade and rebuilt the full logic in Claude Opus 4.6. The strategy, the math, both arb types, the exact 5-step bot architecture - all in the article. Feed it to your OpenClaw, let it spec the bot for Claude Opus 4.6, and you are set.

may.crypto {🦅}

998,611 次观看 • 6 个月前

When I first joined Rayadas I didnt know what it will mean for me as a player! I knew it would be a place I could compete for titles, but I never knew how the passion for this institution would change me as a player. Over the years I learned what it meant to put on this jersey! The people in this city and my team taught me. I feel exactly what the people feel! The love and passion is indescribable, and when you step onto that field you feel it. The people in the stadium make you feel it, and it’s honestly one of the best feelings in this world! That’s why we fight until the very end, because we have a responsibility to represent everything this institution stands for!🙏🏾 #creersiemprecreer
0:13

When I first joined Rayadas I didnt know what it will mean for me as a player! I knew it would be a place I could compete for titles, but I never knew how the passion for this institution would change me as a player. Over the years I learned what it meant to put on this jersey! The people in this city and my team taught me. I feel exactly what the people feel! The love and passion is indescribable, and when you step onto that field you feel it. The people in the stadium make you feel it, and it’s honestly one of the best feelings in this world! That’s why we fight until the very end, because we have a responsibility to represent everything this institution stands for!🙏🏾 #creersiemprecreer

Jermaine Seoposenwe

108,602 次观看 • 1 年前

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓
0:16

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓

Argona

38,189 次观看 • 1 个月前

I found another area of interest that the elites have occupied. This time, it features a large restricted military zone, extensive tunnels and underground facilities. It is located on one of the oldest and most stable cratons, also known as the "survivor continents," and, most importantly, it has one of the strongest magnetic anomalies! Find out the location and the continent by subscribing to my X account or Patreon. This is one of a series of posts in which I reveal what I believe are their safe locations for the event.
0:18

I found another area of interest that the elites have occupied. This time, it features a large restricted military zone, extensive tunnels and underground facilities. It is located on one of the oldest and most stable cratons, also known as the "survivor continents," and, most importantly, it has one of the strongest magnetic anomalies! Find out the location and the continent by subscribing to my X account or Patreon. This is one of a series of posts in which I reveal what I believe are their safe locations for the event.

Open Minded Approach

175,156 次观看 • 2 个月前

$1,500 → $33,000 on 5min BTC markets in 2 days This is the new reality. It stops being gambling the moment you define an exact algorithm. Here are the recommendations on how to create the same trading bot: → Write your code in Rust – it offers C++ level speed, and there’s an official polymarket-client-sdk available. → Minimize Latency – your trading bot must be deployed in the same data center as Polymarket: AWS eu-west-2 (London). This ensures the lowest possible execution lag. → Price Discovery – Polymarket pulls prices from Chainlink, but Chainlink doesn’t "create" the price; it simply aggregates and broadcasts it. Use Binance – as the largest spot exchange, it is the primary source of price discovery. → Apply the Black-Scholes Model for binary options – this is exactly what will help you identify +EV opportunities by calculating all necessary Greeks and variables. → Don’t turn it into a casino – use the Kelly Criterion. It acts as your risk manager, calculating the optimal % of your bankroll for every single position. If you want to earn like trading bot devs – you need to think like them.
0:15

$1,500 → $33,000 on 5min BTC markets in 2 days This is the new reality. It stops being gambling the moment you define an exact algorithm. Here are the recommendations on how to create the same trading bot: → Write your code in Rust – it offers C++ level speed, and there’s an official polymarket-client-sdk available. → Minimize Latency – your trading bot must be deployed in the same data center as Polymarket: AWS eu-west-2 (London). This ensures the lowest possible execution lag. → Price Discovery – Polymarket pulls prices from Chainlink, but Chainlink doesn’t "create" the price; it simply aggregates and broadcasts it. Use Binance – as the largest spot exchange, it is the primary source of price discovery. → Apply the Black-Scholes Model for binary options – this is exactly what will help you identify +EV opportunities by calculating all necessary Greeks and variables. → Don’t turn it into a casino – use the Kelly Criterion. It acts as your risk manager, calculating the optimal % of your bankroll for every single position. If you want to earn like trading bot devs – you need to think like them.

lunatik

93,343 次观看 • 6 个月前

SOMEONE BUILT A TERMINAL TORRENT CLIENT THAT SEARCHES EVERY TRUSTED SOURCE AT ONCE AND DOWNLOADS STRAIGHT TO DISK finding a torrent in 2026 is miserable fake download buttons, popups that spawn three more tabs, and half the results are dead with zero seeders. so he built the opposite of all that: > type one query and it hits a curated set of trackers all at once > results stream back tagged with source, size and seeders as fast as each site answers > arrow to the one you want, press d, and it lands on your drive > if one source is down it just skips it and keeps searching the rest > downloads run in the background and pick up where they left off if you quit mid transfer the whole thing is one command. npx and youre running, all you need is node, no browser, no setup, nothing leaves your machine except the request itself. its called torlink, open source and mit. this is the kind of clean terminal tool that does one annoying thing perfectly
0:16

SOMEONE BUILT A TERMINAL TORRENT CLIENT THAT SEARCHES EVERY TRUSTED SOURCE AT ONCE AND DOWNLOADS STRAIGHT TO DISK finding a torrent in 2026 is miserable fake download buttons, popups that spawn three more tabs, and half the results are dead with zero seeders. so he built the opposite of all that: > type one query and it hits a curated set of trackers all at once > results stream back tagged with source, size and seeders as fast as each site answers > arrow to the one you want, press d, and it lands on your drive > if one source is down it just skips it and keeps searching the rest > downloads run in the background and pick up where they left off if you quit mid transfer the whole thing is one command. npx and youre running, all you need is node, no browser, no setup, nothing leaves your machine except the request itself. its called torlink, open source and mit. this is the kind of clean terminal tool that does one annoying thing perfectly

Om Patel

361,539 次观看 • 2 个月前

there is so much real data just sitting in the open right now it's almost funny. four years of starlight on every star, a NASA archive that's been free for over a decade, detectors still recording the sky tonight, and barely anyone has a net pointed at any of it. so i pointed one. this is me pulling the planet data, the data loading is the boring part. the net i built to read it, the wall it hit, and what that taught me about where AI goes next, that's the full story, and it drops tonight. the data's public, the tools are free, the box fits on a desk. what's stopping you. you can just do things anon.
0:11

there is so much real data just sitting in the open right now it's almost funny. four years of starlight on every star, a NASA archive that's been free for over a decade, detectors still recording the sky tonight, and barely anyone has a net pointed at any of it. so i pointed one. this is me pulling the planet data, the data loading is the boring part. the net i built to read it, the wall it hit, and what that taught me about where AI goes next, that's the full story, and it drops tonight. the data's public, the tools are free, the box fits on a desk. what's stopping you. you can just do things anon.

Sudo su

60,445 次观看 • 3 个月前

$14,000 a month, and the only thing that isn't real is the girls The followers are real, the likes are real, the revenue is real > three TikTok accounts, 45,000, 95,000, and 145,000 followers > over 6 million likes, one video at 2.4 million views > all three on OnlyFans at $19.99 a month > $50 for a personal message, the reply comes from ChatGPT A guy I know built all of it in five months from one free evening the audience never met anyone, because there's no one to meet, and they pay anyway
0:11

$14,000 a month, and the only thing that isn't real is the girls The followers are real, the likes are real, the revenue is real > three TikTok accounts, 45,000, 95,000, and 145,000 followers > over 6 million likes, one video at 2.4 million views > all three on OnlyFans at $19.99 a month > $50 for a personal message, the reply comes from ChatGPT A guy I know built all of it in five months from one free evening the audience never met anyone, because there's no one to meet, and they pay anyway

Kiyoro

20,358 次观看 • 2 个月前